scholarly journals Dealing with Multicollinearity Problem in Analysis of Side Friction Characteristics Under Urban Heterogeneous Traffic Conditions

2021 ◽  
Author(s):  
Shishodiya Ghanshyam Singh ◽  
S. Vasantha Kumar
Keyword(s):  
Linear Combination ◽  
Regression Models ◽  
Heterogeneous Traffic ◽  
Independent Variables ◽  
Traffic Characteristics ◽  
Vehicular Speed ◽  
Inflation Factor ◽  
Highly Correlated ◽  
Side Friction ◽  
The Impact

AbstractDisturbance to the moving traffic, such as on-street parking and bus stop on carriageway normally called as side friction in the literature, is one of the major problems that impact the vehicular speed on urban arterials in developing countries like India. Regression model to study the mode-wise vehicular speeds using side friction and other influencing variables faces the problem of multicollinearity as there is a strong correlation between the independent variables which results in high R2 and high p values. Instead of dropping the highly correlated variables which is the conventional practice to deal with multicollinearity, we proposed an approach of taking a linear combination and ratio of independent variables. To test the applicability of the proposed approach, traffic data from five locations in Hyderabad and Vellore in India having a wide variety of geometric and traffic characteristics with one or more side frictions were collected and regression models were built. It was found that the proposed approach of taking linear combination and ratio worked very well as the models exhibited a high R2, low p values and low variance inflation factor. The regression models also forecast speeds with good and reasonable accuracy. For better understanding of the impact of side friction, the present study proposed an index called side friction index and it was found that the number of side friction elements and their impact are directly proportional. Also, the impact is not uniform across the different vehicle types. Though the present study focussed on side friction problem, the approach that we proposed in this paper to deal with multicollinearity can be applied in other fields as well.

scholarly journals HTPC: heterogeneous traffic-aware partition coding for random packet spraying in data center networks

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Jiawei Huang ◽  
Shiqi Wang ◽  
Shuping Li ◽  
Shaojun Zou ◽  
Jinbin Hu ◽  
...  
Keyword(s):  
Data Center ◽  
Large Scale ◽  
Network Performance ◽  
Rooted Tree ◽  
Heterogeneous Traffic ◽  
Data Center Networks ◽  
Packet Reordering ◽  
Traffic Characteristics ◽  
Network Utilization ◽  
The Impact

AbstractModern data center networks typically adopt multi-rooted tree topologies such leaf-spine and fat-tree to provide high bisection bandwidth. Load balancing is critical to achieve low latency and high throughput. Although the per-packet schemes such as Random Packet Spraying (RPS) can achieve high network utilization and near-optimal tail latency in symmetric topologies, they are prone to cause significant packet reordering and degrade the network performance. Moreover, some coding-based schemes are proposed to alleviate the problem of packet reordering and loss. Unfortunately, these schemes ignore the traffic characteristics of data center network and cannot achieve good network performance. In this paper, we propose a Heterogeneous Traffic-aware Partition Coding named HTPC to eliminate the impact of packet reordering and improve the performance of short and long flows. HTPC smoothly adjusts the number of redundant packets based on the multi-path congestion information and the traffic characteristics so that the tailing probability of short flows and the timeout probability of long flows can be reduced. Through a series of large-scale NS2 simulations, we demonstrate that HTPC reduces average flow completion time by up to 60% compared with the state-of-the-art mechanisms.

scholarly journals Travel Time Estimation Modelling under Heterogeneous Traffic: A Case Study of Urban Traffic Corridor in Surat, India

2018 ◽  
Vol 47 (4) ◽  
pp. 302-308 ◽  
Author(s):  
Krishna Saw ◽  
Aathira K. Das ◽  
Bhimaji K. Katti ◽  
Gaurang J. Joshi
Keyword(s):  
Travel Time ◽  
Heavy Traffic ◽  
Time Estimation ◽  
Urban Traffic ◽  
Heterogeneous Traffic ◽  
Travel Time Estimation ◽  
Estimation Model ◽  
Traffic Condition ◽  
Side Friction ◽  
The Impact

Achievement of fast and reliable travel time on urban road network is one of the major objectives for a transport planner against the enormous growth in vehicle population and urban traffic in most of the metropolitan cities in India. Urban arterials or main city corridors are subjected to heavy traffic flow resulting in degradation of traffic quality in terms of vehicular delays and increase in travel time. Since the Indian roadway traffic is characterized by heterogeneity with dominance of 2Ws (Two wheelers) and 3Ws (Auto rickshaw), travel times are varying significantly. With this in background, the present paper focuses on identification of travel time attributes such as heterogeneous traffic, road side friction and corridor intersections for recurrent traffic condition and to develop an appropriate Corridor Travel Time Estimation Model using Multi-Linear Regression (MLR) approach. The model is further subjected to sensitivity analysis with reference to identified attributes to realize the impact of the identified attributes on travel time so as to suggest certain measures for improvement.

scholarly journals The impact of corporate social responsibility on earnings quality in UK listed firms

2020 ◽  
Vol 9 (3) ◽  
pp. 678-695
Author(s):  
Zuhur Alatawi
Keyword(s):  
Regression Model ◽  
Financial Reporting ◽  
Regression Models ◽  
Earnings Quality ◽  
Listed Firms ◽  
Independent Variables ◽  
Size Growth ◽  
Corporate Social ◽  
The Impact ◽  
The Relationship

A business committed to CSR activities can establish a favourable reputation in the market hence this reputation can be used to mislead the market by making them rely on the financial reporting of the organisation. This study aimed to investigate the relationship between CSR and earnings quality for firms listed on FTSE 350. Besides, it aimed to explore the impact of CSR on the motivation of the management to improve the earnings quality or manage earnings. The research has applied LSDV regression and OLS regression on the data collected from 217 firms listed on the FTSE 350. The respective regression models applied by keeping earnings quality as a dependent variable and range of independent variables such as CSR, SIZE, GROWTH, LEVERAGE and ROA. Besides, the correlation coefficient has also been calculated despite, the result could not reveal the nature of the relationship between the variables hence regression model was applied. The results have revealed no relationship between earnings quality and CSR in the case of LSDV regression model. The same has been observed for the OLS model however, there exists a relatively significant relationship between earnings quality and LEVERAGE. Similar findings recorded for earnings quality and GROWTH.

scholarly journals Regression with Highly Correlated Predictors: Variable Omission Is Not the Solution

2021 ◽  
Vol 18 (8) ◽  
pp. 4259
Author(s):  
Mariella Gregorich ◽  
Susanne Strohmaier ◽  
Daniela Dunkler ◽  
Georg Heinze
Keyword(s):  
Public Health ◽  
Regression Models ◽  
Research Question ◽  
Diagnostic Tools ◽  
Environmental Sciences ◽  
Independent Variables ◽  
Bivariate Correlation ◽  
Highly Correlated ◽  
Correlated Predictors ◽  
Epidemiology And Public Health

Regression models have been in use for decades to explore and quantify the association between a dependent response and several independent variables in environmental sciences, epidemiology and public health. However, researchers often encounter situations in which some independent variables exhibit high bivariate correlation, or may even be collinear. Improper statistical handling of this situation will most certainly generate models of little or no practical use and misleading interpretations. By means of two example studies, we demonstrate how diagnostic tools for collinearity or near-collinearity may fail in guiding the analyst. Instead, the most appropriate way of handling collinearity should be driven by the research question at hand and, in particular, by the distinction between predictive or explanatory aims.

scholarly journals The Impact of Entrepreneurship on Economic Growth within a City

Businesses ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 142-150
Author(s):  
Xiaoyan Huang ◽  
Yuli Chen
Keyword(s):  
Economic Growth ◽  
Gross Domestic Product ◽  
Government Spending ◽  
Regression Models ◽  
Financial Capital ◽  
Moderation Effect ◽  
Independent Variables ◽  
Multiple Regression Models ◽  
The Impact ◽  
The City

Entrepreneurship usually takes place in innovative systems, mostly in cities. Cities, with unique features, may alter the impact of entrepreneurship. This paper employs multiple regression models to assess the impact of entrepreneurship on economic growth, considering the moderation effect of the city context. We use Gross Domestic Product (GDP) as the dependent variable and government spending, labor, fixed and financial capital and entrepreneurship as the independent variables. The data are from the 2003–2017 yearbooks of Zhaoqing, Shantou and Meizhou (three cities with distinct cultural and geographic features in Guangdong, China). We conclude that (1) the three cities’ GDPs highly rely on traditional factors of production (i.e., government spending, labor and fixed and financial capital) rather than entrepreneurship and (2) the city context of Meizhou is relatively unsupportive of its entrepreneurship contributing to the GDP, in comparison with that of Zhaoqing and Shantou. This study adds to the literature by empirically assessing and comparing three cities’ entrepreneurship development in China; it also informs scholars and practitioners of the moderation effect of the city context.

scholarly journals Socio-economic and Demographic Covariates of Infant Mortality in Sub-Saharan Africa: Application of Analysis of Variance (ANOVA) and Multiple Regression Models

2018 ◽  
Vol 5 (7) ◽  
pp. 4849-4863
Author(s):  
Dr. Hadgu Bariagaber
Keyword(s):  
Infant Mortality ◽  
Correlation Matrix ◽  
Regression Models ◽  
Sub Saharan Africa ◽  
Clear Understanding ◽  
Fertility Level ◽  
Independent Variables ◽  
High Infant Mortality ◽  
Sub Saharan ◽  
The Impact

The main thrust of the study is investigate the main socio-economic and demographic antecedents and proximate factors influencing Infant Mortality Levels and Patterns in Sub-Saharan African The source of data of the study is largely from the 2001-2005 UNDP Human Development Reports, National Census Results, DHS data and Demographic survey results of Sub-Saharan African Countries. The analytical techniques include analysis of univariate and bivaraite frequency distributions,  ANOVA, correlation matrix  and Multivariate regression models. Each country is taken as the unit of observation and a total of 42 countries are covered. The dependent variable is the level of Infant Mortality whereas 14 independent variables as the predictors influencing the Infant Mortality conditions are considered.   The model outputs suggested that all the fourteen independent covariates appeared to influence the levels of infant mortality positively or negatively, but in varying values of statistical significance, due to multicollinearity among the independent variables as manifested in the correlation matrix which appear to hinder clear understanding of  the impact of each independent variable on infant mortality. However, the stepwise regression output identified the critical covariates of the infant mortality levels. In conclusion, the study indicated that persistent high infant mortality level in the African -Continent has yet to continue for some decades before coming down to acceptable levels. The main reasons which largely appeared to maintain high Infant Mortality Levels among the Sub-Saharan Countries were noted to be the widespread poverty conditions and low level of health services and education in rural Sub-Saharan Africa. Consequently, the high infant mortality in rural Africa has been observed to be influenced by high fertility level, family planning programmes, education and employment, among other background and proximate variables.

Analisis Pengaruh Penerimaan Pajak Daerah Dan Retribusi Daerah Terhadap Pendapatan Asli Daerah Kabupaten/Kota Di Jawa Tengah

2015 ◽  
Vol 2 (1) ◽  
pp. 51-61
Author(s):  
Beta Asteria
Keyword(s):  
Local Government ◽  
Government Budget ◽  
Multiple Regressions ◽  
Independent Variables ◽  
Central Java ◽  
Directorate General ◽  
Fiscal Balance ◽  
Research Findings ◽  
Local Government Budget ◽  
The Impact

This research deals with the impact of Local Tax and Retribution Receipt to Local Government Original Receipt of Regency/City in Central Java from 2008 to 2012. This research utilizes the data of actual of local government budget from Directorate General of Fiscal Balance (Direktorat Jendral Perimbangan Keuangan). Methods of collecting data through census. The number of Regency/City in Central Java are 35. But the data consists of 33 of Regency/City In Central Java from 2008 to 2012. Total of samples are 165. Karanganyar Regency and Sukoharjo Regency were not included as samples of this research because they didn’t report the data of actual of local government budget to Directorate General of Fiscal Balance in 2009.The model used in this research is multiple regressions. The independent variables are Local Tax and Retribution Receipt, the dependent variable is Local Government Original Receipt. The research findings show that Local Tax and Retribution give the significant impact partially and simultaneusly on Local Government Original Receipt at real level 5 percent. All independent variables explain 91,90 percent of the revenue variability while the rest 8,10 percent is explained by other variables.Keywords: Local Tax, Retribution, and Local Government Original Receipt

Faktor-faktor yang Mempengaruhi Belanja Modal pada Kabupaten atau Kota di Provinsi Sumatera Selatan

2018 ◽  
Vol 2 (1) ◽  
pp. 140
Author(s):  
Gogor Mustawa Zais
Keyword(s):  
Multiple Regression ◽  
Capital Expenditure ◽  
Independent Variables ◽  
The Impact

ABSTRACT The objective of this study was to find out and analyze the impact of regional own revenue (PAD), general allocation fund (DAU) and special allocation fund (DAK) on capital expenditure (BM)  in regencies/towns in South  Sumatera Province  for a period of 2010 to 2014. The data were analyzed by using multiple regression. There were four variables in this research. A dependent variable was capital expenditure (BM) and independent variables were regional own revenue (PAD), general allocation fund (DAU) and special allocation fund (DAK). The results showed that the regional own revenue and special allocation fund variables have positive and significant impact on the capital expenditure. This means that the higher the regional own revenue and special allocation fund, the regencies/towns increased the capital expenditure are also higher. General allocation fund do not have a significant effect on the capital expenditure (BM) in regencies/towns in South Sumatera Province for a period of 2010 to 2014

PENGARUH KUALITAS PELAYANAN DAN KEPERCAYAAN TERHADAP LOYALITAS NASABAH PT BANK MANDIRI,Tbk CABANG JAKARTA KELAPA GADING BARAT

2015 ◽  
Vol 3 (3) ◽  
Author(s):  
Imam Wibowo ◽  
Santi Putri Ananda
Keyword(s):  
Linear Regression ◽  
Service Quality ◽  
Multiple Linear Regression ◽  
Analysis Tool ◽  
Positive Contribution ◽  
Homogeneous Population ◽  
Independent Variables ◽  
Research Population ◽  
The Impact

Purpose-To study the impact of the service quality and trust on customers loyalty of PT.Bank Mandiri,Tbk; Kelapa Gading Barat Branch. To improve the customers loyalty there are several factors that can influence them, such as service quality and trust. Methodology/approach-The research population was all customers PT.Bank Mandiri,Tbk;Kelapa Gading Barat Branch.According to the homogeneous population and based on the Gay and Diehl Theory, the samples taken were 50 people. Variables in this investigations consisted of: a).Independent Variables (exogenous): Service Quality (X1) and Trust (X2). b).The dependent variable (endogenous) Customers Loyalty (Y). Analysis tool being used is multiple linear regression which previously conducted validity and realiability. Findings-The result of investigations that service quality and trust simultaneously have a very strong contribution of 75,5% to the customers loyalty, and partially showed that service quality has significant and positive contribution to the customers loyalty of 64,8%. Partially, the trust variable has significant and positive contribution which amounted to 55,9% to the customers loyalty.

Sign in / Sign up

Export Citation Format

Share Document